Abstract
Gesture recognition using depth and infrared image data has seen the greatest development and is the most acknowledged technological advancement in recent years. It has given rise to contactless scenarios, where the device and system capture changes in user movements and allow more intuitive input gestures. As a result, users need not learn specific knowledge beforehand, and can input commands using natural interaction. Shadow puppetry is an important art form in traditional Chinese arts and cultures, and is a key representation of intangible culture heritage as recognized by the UNESCO. Traditionally, the puppeteers use wooden rods to articulate the puppets’ joints and produce a very stylized form of animation. However, with ever advancing media trend and technologies, the mastery of this art form is in danger of extinction and its popularity is in decline. The goal of this study is to utilize gesture recognition to develop a system to improve upon traditional puppetry manipulation and therefore encourage complete beginners to learn to use it, and lower the barrier to digital medium adoption. In this study both qualitative and quantitative analysis were conducted and yielded positive results.